kb22/Heart-Disease-Prediction

The project involves training a machine learning model (K Neighbors Classifier) to predict whether someone is suffering from a heart disease with 87% accuracy.

51
/ 100
Established

This project helps medical professionals or health data analysts quickly assess the likelihood of heart disease in patients. By inputting patient health metrics, it outputs a prediction of whether heart disease is present. This is designed for healthcare practitioners who need a rapid, data-driven initial screening tool.

266 stars. No commits in the last 6 months.

Use this if you are a clinician or health analyst looking for a quick, automated way to evaluate a patient's risk of heart disease based on their health data.

Not ideal if you need a diagnostic tool for definitive medical conclusions, as this is a predictive model, not a substitute for clinical judgment.

cardiology patient-screening predictive-health medical-risk-assessment
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 10 / 25
Maturity 16 / 25
Community 25 / 25

How are scores calculated?

Stars

266

Forks

194

Language

Jupyter Notebook

License

MIT

Last pushed

Mar 28, 2023

Commits (30d)

0

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